Enhancing Efficiency and Workflow of Bio Statistics Teams

Converting Repeated Processes to a Shiny Suite of Applications for
Reproducibility, Reporting, and Scalability

Mayank Agrawal
Senior R developer Consultant I
ProCogia

Friday, October 27, 2023

Phase 2 Trails

A Phase 2 trial answers the question, “Does Drug X improve Disease Y?”

  • Phase 2 clinical trials assess the safety and efficacy of a new drug or drug combination for a specific medical condition.
  • Goal: Determine appropriate dose and treatment plan for Phase 3 testing.
  • Phase 2a: Involves fewer patients, generally 100-300 patients to focus on dose-response relationships and optimal dosing frequency.
  • Phase 2b: Rigorously assesses drug’s effectiveness in disease treatment, prevention, or diagnosis.
  • Assess therapeutic effectiveness in a specific patient group for potential Phase 3 study.
  • Also used to assess and review safety parameters for potential adverse events that might have been missed in a particular patient group.

Challenges

Dose Simulations for Phase 2 trails are often complex and time consuming with repeated similar workflow steps for each new variation of the dosage trail.

This often leads to

  • Delayed Analysis and reporting
  • Longer study time (years)
  • Delayed Time to Market

resulting in

  • Hindered workflows
  • Lower productivity
  • Repeated boring processes

Key Issues

  • Manual processes
  • Lengthy simulation times
  • Scalability constraints
  • Limited collaboration
  • Reporting challenges
  • Flexibility
  • Reproducibility

Solution

Empowering Biostatisticians with R Shiny suite of applications

  • Collaborated with Biostats to understand their pain points and challenges.
  • Developed a R Shiny application for Phase 2 trails of dosage simulation.
  • Fully scaled through an iterative process of Agile development and feedback.
  • Created multiple R Shiny apps targetted to specific workflows.
  • Developed an ecosystem of Biostatistics R Shiny applications.
  • Automated and improved reporting.
  • Enhanced workflow efficiency and productivity among biostats team.

What was the journey to success?

Migration Process Steps

  • Define scope of each process.
  • Document repetition rate, importance, and time investment for each work request.
  • Identify the most time-consuming, yet simplest workflow.
  • Develop a MVP (Minimum Viable Product)
    • Showcase a demo with the smallest workflow.
    • This aids leaders in visualizing the impact of approval.
  • Integrate workflows incrementally from small to large.

Why Shiny?

  • Helps to build interactive web apps straight from R.
  • Shiny offers dynamic filtering, enabling instant analysis and visualization of data.
  • Shiny is compatible for generating Tables, Listings, and Graphs (TLGs).
  • Enables efficient visualization of complex clinical trial data.
  • Allows for easy exploration of various dosage scenarios.
  • Supports seamless collaboration among trial stakeholders.
  • Enables real-time updates, crucial for adapting to evolving trial needs.
  • Its interactive features enhance decision-making and adaptability for evolving trial needs in Phase 2 trials.
  • Shiny has a quick to moderate learning curve.

Principles of Application Design

  • Showcase early application design outlines using draw.io for UI layout prototyping.
  • Establish a standard application template layout using either Shiny Dashboard, bslib and/or bs4Dash.
    • Create custom R function wrappers based on organization theme and color layout.
    • Re-use the template for new builds and ideas to maintain consistency and coherence.
  • Define the flow of reactivity for the overall application/dashboard.
    • Waterfall Reactivity Model.
    • Avoid Reactivity Spaghetti Mess
    • Leverage reactive dynamic UI elements based on user input to enhance interactivity and responsiveness.

Principles of Application Design

  • Create smaller, independent Proof of Concepts (POCs) for new feature requests.
  • Prioritize user-friendliness: if it’s not intuitive, it won’t be used.
    • Set default selections for input widgets to make application exploration and understanding easier for users.
    • Incorporate tooltips, notifications, sectional write-ups and clear instructions to guide users in using the application.
  • Facilitate Consistent Reporting:
    • Utilize parameterized Markdown/Quarto reports for dynamic MS Word report generation within the application.
    • Adhere to the organization’s document template for uniformity in reporting.
    • Ensure each page or process has a predefined standard write-up with dynamic bits/sections based on simulation calculations.

Streamline Workflow

  • Use RStudio Projects
  • Version Control with Git
    • Use Issues, Pull Requests and Connected Commits for efficient and effortless parallel development.
    • A picture speaks a thousand words. If it can be explained with a screenshot, don’t shy away.
  • Organize your project structure
    • Group related files together for easy navigation.
    • Create, adopt and enforce a standard development template for easier developer onboarding.
    • Have a project template repository for initial cloning.

Ensuring Reproducibility

  • Leverage package management tools
    • Utilize renv or packrat to manage package dependencies.
    • Provides a controlled environment for your project.
    • Ensure reproducibility and minimize version conflicts.
  • Rely on packages published and actively maintained on CRAN for a validated R environment.
  • Establish unit tests for all functions used to ensure accurate and consistent results.
  • Invest time to create an in-depth GitHub ReadMe with the sections Project Overview, Getting Started, User Application Flow and Usage, Key Programming Concept Implemented (if any) and Developer Guide providing comprehensive project reproducibility instructions.

Enhancing Scalability

  • Implement modularization and functional programming for a plug-and-play development format across applications.
  • Enable multiple studies to be added concurrently using standard git branching strategies, involving multiple concurrent developers.
  • Async Programming: Evaluate longer simulations in a separate R process preventing app performance issues.
  • Take a step further and deploy simulation functions as internal APIs with Plumber.
  • Write your custom JavaScript and R bindings for implementing unique feature requests.
  • Approach feature requests as a blend of web development, software engineering, and R development.

Utilize Automated Testing

  • Writing Test Cases (Inputs, Expected Outputs)
  • Full Stack Testing
  • Types of Tests: Unit, Functional, Integration, and End-to-End
  • Continuous Integration for Testing with Git branching strategies.
  • Benefits
    • Early bug detection
    • Efficiency and speed
    • Consistent and repeatable testing
    • Increased test coverage
    • Regression testing capabilities
    • Greater confidence in release stability

Common Application Features

  • Add and execute multiple simulations simultaneously.
  • Compare similar (static and interactive) graphs side by side for comprehensive analysis.
  • Downloadable visualization, simulation calculations, and dynamic FDA submission format reports across the application.
  • Display mathematical equations for each study using LaTeX.
  • Receive email notifications for progress updates along with attached reports.
  • Receive notifications upon process completion.
  • Introduce Helper Tabs for - Application Information, Usage Manual, Release Notes, System Information, User Feedback and Contact Business Lead - all through the application.

Enhancing User Adoption

  • Create multiple GIFs showcasing the application layout and user flow.
    • Include them in the Git readme and announcement emails.
  • Create detailed application interaction user manuals with screenshots and highlights for each step.
  • Conduct regular (quarterly) training sessions to provide guidance, answer questions, and assist users with new features.
    • Record and share them for easier re-visit.
  • Continuously engage user base for better ROI and on boarding.
  • Prioritize most requested user features for each sprint.

Thank you

References - R Packages

R Pharma 2023